Inteligencia Artificial Generativa para Calificar Trabajos Académicos

This paper examines the reliability and validity of generative AI in grading academic assignments. Through a literature review and an empirical study, this paper demonstrates that generative AI platforms are currently not a good choice for grading academic assignments due to their inconsistency and unreliability. The study involved repeatedly submitting 12 different papers with varying levels of proficiency to a generative AI platform, revealing significant inconsistencies in grading outcomes.

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Publication Details

Journal
Journal of the Association for Information Systems
Published
2025-12-31
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
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article

Inteligencia Artificial Generativa para Calificar Trabajos Académicos

Journal of the Association for Information Systems
Geochemistry and Geologic Mapping
article

Inteligencia Artificial Generativa para Calificar Trabajos Académicos

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Abstract

This paper examines the reliability and validity of generative AI in grading academic assignments. Through a literature review and an empirical study, this paper demonstrates that generative AI platforms are currently not a good choice for grading academic assignments due to their inconsistency and unreliability. The study involved repeatedly submitting 12 different papers with varying levels of proficiency to a generative AI platform, revealing significant inconsistencies in grading outcomes.

Journal of the Association for Information Systems
Artelia (France) (FR)
Quality Education
Openalex Percentile: Top 43%
Geochemistry and Geologic Mapping
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Inteligencia Artificial Generativa para Calificar Trabajos Académicos · Journal of the Association for Information Systems (2025) | TGRS Research Map | TGRS